Problems of classification of globular clusters and their systems

A review is carried out mainly of the classification problems of globular clusters (GC) of our Galaxy. Classification of GC has a rich history, since it was first considered by Shapley and Sawyer [1] over 90 years ago. After them, a number of authors [2-8] tried to classify GC in various ways, but however, before our work no one was able to solve this problem to the desired level. We first studied the physical characteristics of the GC of our Galaxy by constructing diagrams of the relationship between these characteristics. Next, we decided to answer the question of whether it is possible to somehow classify GC by the velocity anisotropy parameter. It turned out that this also does not lead to the desired result. In this regard, we decided to model the apparent surface density in the GC in the form of a specific function with three free parameters. One of these parameters $\gamma$, characterizes the degree of concentration of stars to the center of the cluster. We calculated the values of the parameter $\gamma$ for 26 GC by minimizing the difference between the theoretical function and the observed apparent density in the GC, using the symplectic method. In this way, the calculations yielded excellent results that allow us to classify GC according to parameter $\gamma$, and the values of this parameter have a good correlation with the main physical characteristics of GCs given in the Harris catalog. Thus, the classification problem can be sufficiently solved. This good result was obtained thanks, in particular, to the qualitative observational data we used, which are presented in [9]. These authors were able to combine the CCD observations of the Hubble Space Telescope and wide-field terrestrial data to obtain stellar surface density profiles for the GC stars. Further, we note that no one tried to somehow classify GC systems, although there is a good catalog of GC systems, also made by W. Harris [10]. The problem of classification of GC systems turned out to be more difficult than the classification of GC themselves. In our opinion, this difference is primarily associated with the quality of observational data.

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